Tian Qiu

Background/Objectives: Plant-based diets are widely recommended for lowering the risk of type 2 diabetes, with the caveat that their health benefits depend on the quality of the foods consumed. This analysis examined associations between five dietary patterns and pre-existing diabetes among patients with acute pancreatitis (AP), a population in which the relationship between diet and diabetes has not been well characterized. Methods: Participants were drawn from the Diabetes RElated to Acute Pancreatitis and its Mechanisms (DREAM) study, an ongoing multicenter study of adults aged 18 to 75 years with AP in the U.S. This cross-sectional analysis evaluated five dietary patterns using food frequency questionnaires (FFQ): the reverse Empirical Dietary Index for Hyperinsulinemia (rEDIH), the reverse Empirical Dietary Inflammatory Pattern (rEDIP), the overall plant-based diet index (PDI), the healthful plant-based diet index (hPDI), and the unhealthful plant-based diet index (uPDI). We used multivariable logistic regression models to estimate odds ratios (ORs) for pre-existing diabetes (i.e., prior to the AP episode). Results: A total of 647 participants (mean age 49.1 ± 14.5 years) were included. In multivariable-adjusted analyses, participants in the highest versus lowest tertile of PDI had 55% lower odds of pre-existing diabetes (adjusted OR: 0.45; 95% CI: 0.25–0.80; p-trend = 0.005). No statistically significant associations were detected for rEDIP, rEDIH, hPDI, or uPDI. Conclusions: Higher overall PDI scores were associated with lower odds of prevalent diabetes. Among patients with AP, further studies are needed to evaluate dietary contributions to future diabetes development following AP and identify potential dietary strategies for diabetes prevention.

Introduction: Acute pancreatitis (AP) is a common inflammatory disorder that is associated with increased risk for diabetes mellitus (DM). It remains unclear whether recurrent acute pancreatitis (RAP) is associated with further increased risk of incident DM. This study aims to investigate the association between RAP and incident DM using real-world data. Methods: We conducted a retrospective cohort study using the Merative ^TM MarketScan® claims database (2016–2023), identifying patients with AP and no prior history of DM at baseline. The primary exposure of interest, RAP, was defined as one or more episodes of AP occurring ≥90 days after the index AP diagnosis, whereas one episode of AP referred to a single episode of AP (SAP) with no subsequent recurrence within 90 days following the index event. A multivariable stratified Cox proportional hazards regression models were used to determine the association between RAP and incident DM, identified using ICD-10 codes. Results: In total, 16,184 individuals with AP (mean [SD] age: 45.8 [12.3]) contributed 40,712 person-years of follow-up, during which 1,477 incident cases of DM were documented. Individuals with RAP had an increased risk of incident DM compared with those with a SAP(adjusted HR, 1.92; 95% CI, 1.61-2.29). The risk increased significantly with the frequency of RAP. In comparing the modifying effect of patient demographics and comorbidities, a stronger association between RAP and incident DM was observed in females (adjusted HR, 2.44; 95% CI, 1.87-3.19) than in males (adjusted HR, 1.64; 95% CI, 1.30-2.07; P _interaction =0.03). Also, stronger associations were observed among younger patients (18–46 y) (adjusted HR=2.56; 95% CI, 1.97-3.31) and among non-tobacco abuse (adjusted HR=2.19; 95% CI, 1.81-2.65), with significant interactions for all comparisons ( P _interaction <0.05 Conclusions: In this real-world study, RAP was associated with an increased risk of incident DM. Our findings highlight an opportunity for glycemic monitoring and proactive management of patients with RAP to mitigate their risk of developing DM.

Introduction: About one-quarter of patients with acute pancreatitis (AP) will develop diabetes mellitus (DM) within 3 years, but risk factors remain unclear. This study aims to determine whether machine learning models (ML) can be trained to accurately predict new-onset DM following AP and identify key clinical features using real-world data. Methods: This retrospective cohort study used de-identified data from the TriNetX federated electronic health records (EHR) network from 1 January 2017 to 11 March 2024. A total of 58 746 patients with AP (International Classification of Diseases-10 code K85) and no prior diagnosis of DM were included. New-onset DM following AP was the main outcome of interest. Five ML models were trained across four prediction windows, including logistic regression (LR), eXtreme Gradient Boosting, Adaptive Boosting, Random Forest and support vector machine. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC). Results: Among the 58 746 patients with AP (mean (SD) age, 50.2 (16.6) years), the LR model demonstrated the highest overall performance, with a mean accuracy of 0.72 (SD, 0.009) and an AUROC of 0.79 (SD, 0.009). Key clinical features across models included age, pancreatic necrosis, body weight, body mass index, systolic blood pressure, number of medical visits and prior AP laboratory values such as glucose, anion gap, blood urea nitrogen (BUN) and total protein. Conclusions: In this first real-world evidence study using EHR data, we have developed and demonstrated the feasibility of using ML to predict the new onset of DM after AP. Clinical features such as age, pancreatic necrosis, prior glucose, BUN and anion gap had the highest overall importance scores and may inform tailored prevention strategies.

Dietary patterns have been associated with altered risk of diabetes mellitus (DM) in the general population. These patterns can estimate habitual intake of food groups associated with decreased or increased (e.g., greater intake of red meats) risk of DM. This analysis aimed to examine the underexplored associations of four dietary patterns in patients presenting with an acute pancreatitis (AP) diagnosis based on the presence of pre-existing DM. Study participants were selected from the Diabetes RElated to Acute Pancreatitis and its Mechanisms (DREAM) study, an ongoing, multicenter study of adults (18–75 years) with AP in the US. This is a cross-sectional analysis of baseline data collected using the VioScreen computer-administered Food Frequency Questionnaire. We examined four dietary patterns: the Alternate Mediterranean Diet (AMED), the Mediterranean-DASH Diet Intervention for Neurodegenerative Delay (MIND), the Healthy Eating Index-2020 (HEI-2020), and the Alternate Healthy Eating Index-2010 (AHEI-2010). Multivariable logistic regression was used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs). The study population included 647 individuals with AP (mean (SD) baseline age, 49.1 (14.5) years). Participants in the highest tertile of dietary index scores were more likely to be older, female, non-Hispanic White, and to have higher educational attainment. In multivariable analyses, greater adherence to the AMED and the MIND dietary patterns was associated with lower odds of pre-existing DM. Multivariable ORs for the odds of pre-existing DM comparing the highest to lowest tertile of diet scores were 0.44 (95% CI: 0.23, 0.84; P-trend = 0.01) for AMED, 0.46 (95% CI: 0.26, 0.82; P-trend = 0.01) for MIND, indicating lower odds for participants with a healthier dietary pattern. In this analysis, greater adherence to selected healthy dietary patterns was associated with lower odds of pre-existing DM at the time of AP presentation. The online version contains supplementary material available at 10.1186/s12937-026-01294-x.

Greater consumption of red meat has been linked to a higher risk of mortality and chronic diseases, including diabetes. We aim to examine the associations between total, processed and unprocessed red meat intake and diabetes and to evaluate the substitution effects of other protein sources for red meat on diabetes. This population-based cross-sectional study utilised data from the National Health and Nutrition Examination Survey (NHANES) 2003–2016. Diabetes was defined as a self-reported diagnosis by a physician or other health professional, having a fasting plasma glucose of 126 mg/dl or higher, an HbA1c level of 6·5 % or higher, or the use of antidiabetic drugs. Multivariable logistic regression models were conducted. The study included 34 737 adult participants (mean ( sd ) age of 45·8 (17·5) years) from NHANES 2003–2016. After adjusting for major confounders, compared with the first quintile, higher intakes of total, processed and unprocessed red meat were positively associated with higher odds of diabetes, with adjusted OR of 1·49 (95 % CI 1·22, 1·81), 1·47 (95 % CI 1·17, 1·84) and 1·24 (95 % CI 1·06, 1·44), respectively. The corresponding P -trend values were (< 0.001, 0.001, and 0.006). In this nationally representative sample of US adults, participants in the highest quintiles of total, processed and unprocessed red meat intake had higher odds of diabetes than those in the lowest quintile. Substituting 1 serving/d of dietary protein from foods of plant origin (including nuts, seeds, legumes and soya) for total, processed or unprocessed red meat was associated with 9 % to 14 % lower odds of diabetes.

Introduction: Acute pancreatitis (AP) is an inflammatory disease of the exocrine pancreas characterized by tissue damage and sometimes necrosis. However, whether severe AP is associated with an increased risk of incident diabetes remains unclear based on real-world data. This study aims to examine the relationship between severe AP and new-onset diabetes after hospitalization. Methods: We conducted a retrospective cohort study using the Merative™ MarketScan® claims database (2016–2023), identifying patients with AP and no prior history of diabetes at baseline. The exposure, severe AP, was defined by any of the following during hospitalization: pancreatic necrosis, hemodialysis, organ failure, or mechanical ventilation. We used multivariable stratified Cox proportional hazards regression models with propensity score strata to assess the association between severe AP and incident diabetes. Results: The matched study population consisted of 2,046 patients with severe AP and 2,046 patients with mild AP, with baseline characteristics well balanced between groups. Individuals with severe AP had a higher risk of developing diabetes compared with those with mild AP [adjusted hazard ratio (aHR) = 1.64, 95% confidence interval (CI): 1.30–2.06], after accounting for propensity score matching. The association between severe AP and incident diabetes was stronger in men (aHR = 2.03, 95% CI: 1.50–2.74) than in women (aHR = 1.06, 95% CI: 0.69–1.64; P - _interaction = 0.02). Discussion: In this large real-world data study, severe AP was associated with an increased risk of developing diabetes. These findings underscore the importance for glycemic surveillance and the need to consider proactive management of severe AP patients to mitigate their risk of poor health outcomes.

Background: Multiple independent lines of research on self-regulation point to executive cognitive ability (executive function/cognitive control) as a factor that underlies the capacity to successfully regulate one’s thoughts, emotions, and behavior. Critically, while leading theories point to the role of executive control in modifying “in-the-moment” regulatory processes (eg, enacting physical activity, resisting a poor dietary choice, reflecting on a stressful experience), few studies have tested the executive hypothesis at this timescale. Moreover, given the normative changes in executive control across the adult lifespan, it is essential to understand how cognitive aging might impact these processes. Objective: The Physical Activity, Imaging, and Ambulatory Testing (PHIAT) project was designed to test how variation in executive control at multiple timescales (from moment-to-moment within days to age differences across decades) influences self-regulation across the adult lifespan. Methods: A 14-day, high-frequency, ambulatory assessment protocol was designed for this study. The study was conducted in a measurement burst design and included a 14-day ecological momentary assessment (EMA) protocol involving 6 assessments per day. Ultra-brief ambulatory cognitive assessments of multiple domains of cognition were included in the EMA protocol. Throughout the measurement burst, participants also wore 3 activity monitors on the hip, thigh, and wrist to measure physical activity/exercise, measure sedentary behavior, and self-monitor physical activity behavior, respectively. Results: A total of 221 participants ranging from 18 to 89 years of age completed the PHIAT protocol over the course of 2021-2024, and data collection is complete. EMA data were collected from participants reflecting a wide range of psychosocial factors surrounding participation in health-promoting behaviors (motivation, intention, stress, built environment, and social cognitive factors). This EMA data stream is complemented by data from high-frequency, ambulatory cognitive assessments measuring processing speed, working memory capacity, inhibitory control, and divided/sustained attention administered 5 times per day throughout the 14-day burst. In addition, health-promoting behaviors, including sleep, diet, hydration, physical activity, and exercise, were assessed throughout the 14-day burst through a combination of EMA self-report and continuous activity monitoring. Conclusions: A rich, high-frequency dataset was generated by the PHIAT project that will provide a range of novel insights into the motivational factors, information processing, and environmental factors that surround self-regulation of health-promoting behavior.

Background: Multiple, independent lines of research on self-regulation point to executive cognitive ability (executive function/cognitive control) as a factor that underlies the capacity to successfully regulate one’s thoughts, emotion, and behavior. Critically, while leading theories point to the role of executive control in modifying ‘in-the-moment’ regulatory processes (e.g., enacting physical activity, resisting a poor dietary choice, reflecting on a stressful experience), few studies have tested the executive hypothesis at this timescale. Moreover, given normative changes in executive control across the adult lifespan, it is essential to understand how cognitive aging might impact these processes. Objective: The Physical Activity, Imaging, and Ambulatory Testing (PHIAT) project was designed to test how variation in executive control at multiple timescales (from moment-to-moment within-days to age-differences across decades) influences self-regulation across the adult lifespan. Methods: A 14-day, high-frequency, ambulatory assessment protocol was designed for the current study. The study was conducted in a measurement burst design and included a 14-day ecological momentary assessment (EMA) protocol involving 6 assessments per day. Ultra-brief ambulatory cognitive assessments of multiple domains of cognition were included in the EMA protocol. Throughout the measurement burst, participants also wore 3 activity monitors on the hip, thigh, and wrist to measure physical activity/exercise, sedentary behavior, and to self-monitor physical activity behavior, respectively. Results: A total of N=221 participants ranging from 18-89 years of age completed the PHIAT protocol over the course of 2021 to 2024. EMA data was collected from participants reflecting a wide range of psychosocial factors surrounding participation in health-promoting behaviors (motivation, intention, stress, built environment, social cognitive factors). This EMA data stream is complemented by data from high-frequency, ambulatory cognitive assessments measuring processing speed, working memory capacity, inhibitory control, and divided/sustained attention administered 5 times per day throughout the 14-day burst. In addition, health promoting behaviors, including sleep, diet, hydration, physical activity, and exercise, were assessed throughout the 14-day burst through a combination of EMA self-report and continuous activity monitoring. Conclusions: A rich, high-frequency dataset was generated by the PHIAT project that will provide a range of novel insights into the motivational, information processing, and environmental factors that surround self-regulation of health-promoting behavior.

Background: Prior study reported that mushroom consumption was associated with a lower incidence of hyperuricemia, but there is limited evidence on this association. We conducted a collaborative study to investigate the association between mushroom intake and hyperuricemia in middle-aged and older populations. Methods: We used data from the National Health and Nutrition Examination Survey (NHANES) in the U.S. (2007–2018) and the National Institute for Longevity Sciences-Longitudinal Study of Aging (NILS-LSA) in Japan (1997–2012). Consumption of mushroom (g/day) were measured by one- or two-day dietary recall in NHANES and by 3-day dietary records in the NILS-LSA. Hyperuricemia was defined using uric acid levels as > 420 μmol/L and > 350 μmol/L in NHANES for men and women, respectively; in the NILS-LSA, serum uric acid was repeatedly measured at baseline and follow-up surveys. Hyperuricemia was defined as uric acid levels > 416.4 μmol/L for men and ≥ 356.9 μmol/L for women. Logistic regression models in NHANES (cross-sectionally) and Generalized Estimation Equations in NILS-LSA (longitudinally) were performed. Results: A total of 5,778 NHANES participants (mean (SD) age: 53.2 (9.6) years) and 1,738 NILS-LSA (mean (SD) age: 53.5 (11.2) years) were included. Mushrooms were consumed by 5.7% of participants in NHANES and 81.2% in NILS-LSA. We did not observe a significant association between mushroom intakes and hyperuricemia in the NHANES men and women. However, in the NILS-LSA, compared to non-consumers, a higher mushroom intake was associated with a lower risk of incident hyperuricemia in men under 65 years old. The adjusted odds ratio (95% CI) for non-consumers, participants with middle, and the highest consumption of mushrooms were 1.00 (Ref.), 0.77 (0.44, 1.36), and 0.55 (0.31, 0.99), respectively (P-trend = 0.036). No association was found in women in NILS-LSA. Conclusions: Mushroom consumption was associated with a lower risk of incident hyperuricemia in Japanese men.